Name
Abstract | ||
|---|---|---|
This study investigates two-stage plans based on nonparametric procedures for estimating an inverse regression function at a given point. Specifically, isotonic regression is used at stage one to obtain an initial estimate followed by another round of isotonic regression in the vicinity of this estimate at stage two. It is shown that such two-stage plans accelerate the convergence rate of one-stage procedures and are superior to existing two-stage procedures that use local parametric approximations at stage two when the available budget is moderate and/or the regression function is "ill-behaved." Both Wald- and likelihood ratio-type confidence intervals for the threshold value of interest are investigated and the latter are recommended in applications due to their simplicity and robustness. The developed plans are illustrated through a comprehensive simulation study and an application to car fuel efficiency data. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1080/00401706.2014.940773 | TECHNOMETRICS |
Keywords | Field | DocType |
Experimental design,Isotonic regression,Two-stage plan | Econometrics,Inverse,Monotonic function,Mathematical optimization,Isotonic regression,Robustness (computer science),Nonparametric statistics,Parametric statistics,Rate of convergence,Statistics,Confidence interval,Mathematics | Journal |
Volume | Issue | ISSN |
57.0 | 3.0 | 0040-1706 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| runlong tang | 1 | 0 | 0.34 |
| moulinath banerjee | 2 | 1 | 1.06 |
| George Michailidis | 3 | 303 | 35.19 |
| Shawn Mankad | 4 | 27 | 4.42 |